Instructions to use Jfk666/Marcia with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use Jfk666/Marcia with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("<base-model-id>") model.load_adapter("Jfk666/Marcia", set_active=True) - Notebooks
- Google Colab
- Kaggle
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Download README.md from Jfk666/Marcia: direct link, hf CLI and curl.
- Browser
- Download file 401 Bytes
-
https://huggingface.co/Jfk666/Marcia/resolve/main/README.md
- Command line
-
hf download hf://Jfk666/Marcia/README.md
-
curl -L -H "Authorization: Bearer $HF_TOKEN" -o README.md https://huggingface.co/Jfk666/Marcia/resolve/main/README.md
401 Bytes
metadata
datasets:
- Congliu/Chinese-DeepSeek-R1-Distill-data-110k
- open-r1/OpenR1-Math-220k
- open-thoughts/OpenThoughts-114k
- facebook/natural_reasoning
- frascuchon/facebook_natural_reasoning_2
language:
- en
- es
metrics:
- accuracy
base_model:
- microsoft/OmniParser-v2.0
new_version: microsoft/Phi-4-multimodal-instruct
pipeline_tag: visual-question-answering
library_name: adapter-transformers